More than 50,000 single-cell genomes are sequenced in a single run using droplet barcoding. The application of single-cell genome sequencing to large cell populations has been hindered by technical challenges in isolating single cells during genome preparation. Here we present single-cell genomic sequencing (SiC-seq), which uses droplet microfluidics to isolate, fragment, and barcode the genomes of single cells, followed by Illumina sequencing of pooled DNA. We demonstrate ultra-high-throughput sequencing of >50,000 cells per run in a synthetic community of Gram-negative and Gram-positive bacteria and fungi. The sequenced genomes can be sorted in silico based on characteristic sequences. We use this approach to analyze the distributions of antibiotic-resistance genes, virulence factors, and phage sequences in microbial communities from an environmental sample. The ability to routinely sequence large populations of single cells will enable the de-convolution of genetic heterogeneity in diverse cell populations.

We describe droplet microfluidic strategies used to fabricate advanced microparticles that are useful structures for the encapsulation and release of actives; these strategies can be further developed to produce microparticles for advanced drug delivery applications. Microfluidics enables exquisite control in the fabrication of polymer vesicles and thermosensitive microgels from single and higher-order multiple emulsion templates. The strategies used to create the diversity of microparticle structures described in this review, coupled with the scalability of microfluidics, will enable fabrication of large quantities of novel microparticle structures that have potential uses in controlled drug release applications.

Single-cell analysis of CNS interactions: Despite their importance in the physiology and pathology of the central nervous system (CNS), few methods are available for the unbiased, systematic investigation of cell-to-cell interactions at single-cell resolution. Clark et al. developed RABID-seq, a method that combines barcoded viral tracing with single-cell RNA sequencing (see the Perspective by Silvin and Ginhoux). RABID-seq identified the axon guidance molecules Sema4D-PlexinB2 and EphrinB3-EphB3 as mediators of microglia-astrocyte interactions that promote CNS pathology in experimental autoimmune encephalomyelitis and, potentially, multiple sclerosis. These studies also identified candidate therapeutic molecules for the modulation of microglia-astrocyte interactions in multiple sclerosis. Science , this issue p. eabf1230 ; see also p. 342

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Significance: As powerful biological catalysts, enzymes can solve challenging problems that range from the industrial production of chemicals to the treatment of human disease. The ability to design new enzymes with tailor-made chemical functions would have a far-reaching impact. However, this important capability has been limited by our cursory understanding of enzyme catalysis. Here, we report a method that uses unbiased empirical analysis to dissect the molecular basis of enzyme function. By comprehensively mapping how changes in an enzyme’s amino acid sequence affect its activity, we obtain a detailed view of the interactions that shape the enzyme function landscape. Large, unbiased analyses of enzyme function allow the discovery of new biochemical mechanisms that will improve our ability to engineer custom biocatalysts.